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What is Threagile?

Threagile provides teams with a straightforward solution for implementing Agile Threat Modeling, effortlessly fitting into DevSecOps processes. This open-source toolkit enables users to outline an architecture and its components in a flexible, declarative style through a YAML file, which can be modified directly within an IDE or any editor compatible with YAML. Upon execution of the Threagile toolkit, it evaluates a set of risk rules that assess the security of the architecture model, producing a detailed report that highlights potential weaknesses and offers recommended mitigation measures. Furthermore, it generates visually engaging data-flow diagrams and supports output in multiple formats, including Excel and JSON, to facilitate further examination. The tool also incorporates continuous risk management within the Threagile YAML model file, allowing teams to effectively monitor their risk mitigation efforts. Threagile can be conveniently run via the command line, and users have the option to utilize a Docker container or configure it as a REST server for enhanced accessibility. This range of deployment options guarantees that teams can select the setup that aligns best with their specific development environment and workflow requirements. By integrating these functionalities, Threagile significantly enhances the overall security posture of development projects.

What is Ludwig?

Ludwig is a specialized low-code platform tailored for crafting personalized AI models, encompassing large language models (LLMs) and a range of deep neural networks. The process of developing custom models is made remarkably simple, requiring merely a declarative YAML configuration file to train sophisticated LLMs with user-specific data. It provides extensive support for various learning tasks and modalities, ensuring versatility in application. The framework is equipped with robust configuration validation to detect incorrect parameter combinations, thereby preventing potential runtime issues. Designed for both scalability and high performance, Ludwig incorporates features like automatic batch size adjustments, distributed training options (including DDP and DeepSpeed), and parameter-efficient fine-tuning (PEFT), alongside 4-bit quantization (QLoRA) and the capacity to process datasets larger than the available memory. Users benefit from a high degree of control, enabling them to fine-tune every element of their models, including the selection of activation functions. Furthermore, Ludwig enhances the modeling experience by facilitating hyperparameter optimization, offering valuable insights into model explainability, and providing comprehensive metric visualizations for performance analysis. With its modular and adaptable architecture, users can easily explore various model configurations, tasks, features, and modalities, making it feel like a versatile toolkit for deep learning experimentation. Ultimately, Ludwig empowers developers not only to innovate in AI model creation but also to do so with an impressive level of accessibility and user-friendliness. This combination of power and simplicity positions Ludwig as a valuable asset for those looking to advance their AI projects.

Media

Media

Integrations Supported

Docker
Aim
Alpaca
Comet
Discord
Hugging Face
JSON
Kubernetes
Llama 2
MLflow
Microsoft Excel
Python
RAY
TensorBoard
Triton
Weights & Biases

Integrations Supported

Docker
Aim
Alpaca
Comet
Discord
Hugging Face
JSON
Kubernetes
Llama 2
MLflow
Microsoft Excel
Python
RAY
TensorBoard
Triton
Weights & Biases

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Threagile

Company Website

threagile.io

Company Facts

Organization Name

Uber AI

Date Founded

2016

Company Location

United States

Company Website

ludwig.ai/latest/

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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Axel ARONIO DE ROMBLAY